Core Principles for AI-Agent Collaboration (Agentic Development Principles)
"AI is the copilot; you are the pilot." AI agents amplify a developer's thinking and take over repetitive work, but final decisions and responsibility always remain with the developer.
When to use this skill
- Confirm the baseline principles at the start of an AI-agent session
- Decide an approach before starting complex work
- Establish a context-management strategy
- Review workflows to improve productivity
- Onboard teammates on how to use AI agents
Principle 1: Divide and Conquer
Core concept
AI performs far better with small, clear instructions than with large, ambiguous tasks.
How to apply
| Bad example | Good example |
|---|---|
| "Build me a login page" | 1. "Create the login form UI component" |
| 2. "Implement the login API endpoint" | |
| 3. "Wire up the authentication logic" | |
| 4. "Write tests" |
Practical pattern: staged implementation
Step 1: Design and validate models/schemas
Step 2: Implement core logic (minimum viable functionality)
Step 3: Connect APIs/interfaces
Step 4: Write and run tests
Step 5: Integrate and refactor
Verification points
- Can each step be verified independently?
- If something fails, can you fix only that step?
- Is the scope small enough for the AI to understand clearly?
Principle 2: Context is Like Milk
Core concept
Context (the AI's working memory) should always be kept fresh and compressed.
- Old, irrelevant information reduces AI performance
- Context drift: mixing topics can reduce performance by 39%
Context-management strategies
Strategy 1: Single-purpose conversations
Tab 1: Authentication system work
Tab 2: UI component work
Tab 3: Test writing
Tab 4: DevOps/deployment work
Strategy 2: HANDOFF.md technique
When the conversation gets long, document the state:
# HANDOFF.md
## Completed work
- Implemented user authentication API
- Implemented JWT issuance logic
## Current status
- Working on token refresh logic
## Next steps
- Implement refresh tokens
- Add logout endpoint
## Notes
- Watch for conflicts with existing session-management code
Strategy 3: Check context state
- Claude:
/context,/clear - Gemini: start a new session
- ChatGPT: start a new chat
Optimization metrics
- Active tools/plugins: keep minimal
- Conversation length: if it gets too long, create HANDOFF.md and start a new session
Principle 3: Choose the Right Level of Abstraction
Core concept
Choose an appropriate abstraction level for the situation.
| Mode | Description | When to use |
|---|---|---|
| Vibe Coding | High-level: focus on overall structure | Rapid prototyping, idea validation, one-off projects |
| Deep Dive | Low-level: go line-by-line through code | Bug fixes, security reviews, performance optimization, production code |
Practical application
When adding a new feature:
1. High abstraction: "Create a user profile page" → understand the overall structure
2. Mid abstraction: "Show me the validation logic for the profile edit form" → review a specific feature
3. Low abstraction: "Explain why this regex fails email validation" → detailed debugging
Principle 4: Automation of Automation
Core concept
If you've repeated the same task 3+ times → find a way to automate it
Then automate the automation process itself
Automation level evolution
| Level | Approach | Example |
|---|---|---|
| 1 | Manual copy/paste | ChatGPT → terminal |
| 2 | Terminal integration | Use Claude Code, Gemini CLI directly |
| 3 | Voice input | Speech-to-text system |
| 4 | Automate repeated instructions | Use project instruction files |
| 5 | Workflow automation | Custom commands/skills |
| 6 | Decision automation | Use AI skills |
| 7 | Enforced-rule automation | Hooks/Guard Rails |
Identify automation targets
- Do you run the same command 3+ times?
- Do you repeat the same explanations?
- Do you often write the same code patterns?
Principle 5: Plan Mode vs Execute Mode
Plan mode (Plan First)
Analyze only; do not modify anything
When to use:
- Complex work you're doing for the first time
- Large refactors spanning multiple files
- Architecture changes
- Database migrations
Execute mode (Just Do It)
When to use:
- Simple, clear tasks
- Experimental prototypes
- Repetitive, time-consuming work
- Always use in a safe environment (containers, etc.)
Recommended ratio
- Plan mode: 90% (use as the default)
- Execute mode: 10% (only in a safe environment)
Principle 6: Verification and Retrospectives
How to verify outputs
-
Write tests
"Write tests for this function, including edge cases." -
Visual review
- Review changed files via diff
- Revert unwanted changes
-
Create a draft PR
"Create a draft PR." -
Ask for self-verification
"Review the code you just generated again. Verify every claim, and end with a table summarizing verification results."
Verification checklist
- Does the code behave as intended?
- Are edge cases handled?
- Are there any security vulnerabilities?
- Are tests sufficient?
Applying a Multi-Agent Workflow
Role split by agent
| Agent | Role | Best For |
|---|---|---|
| Claude | Orchestrator | Planning, code generation, skill interpretation |
| Gemini | Analyst | Large-context analysis (1M+ tokens), research |
| Codex | Executor | Command execution, builds, deployments |
Orchestration pattern
[Planning agent] Plan → [Analysis agent] Analyze/research → [Execution agent] Write code → [Verification] Test → [Synthesis] Summarize results
Quick Reference
Six principles summary
1. Divide & conquer → Split into small, clear steps
2. Context → Keep it fresh; single-purpose conversations
3. Abstraction → Vibe ↔ Deep Dive depending on context
4. Automation → Automate after 3 repeats
5. Plan/execute → Plan 90%, execute 10%
6. Verify/retro → Tests, PRs, self-verification
Key questions
- Can I break this work into smaller pieces?
- Is the context still clean?
- Am I using the right level of abstraction?
- Have I repeated this 3+ times?
- Did I plan first?
- Did I verify the result?